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Related Questions
- What are the primary goals of fine-tuning a pre-trained model?
- How does fine-tuning differ from adapting a pre-trained model in terms of model architecture?
- What are the key considerations when deciding whether to fine-tune or adapt a pre-trained model?
- Can you explain the difference between fine-tuning and adapting in terms of model weights?
- How do the training objectives differ between fine-tuning and adapting a pre-trained model?
- What are the implications of fine-tuning versus adapting on the model's performance and generalizability?
- Can you provide an example use case where fine-tuning is more suitable than adapting a pre-trained model?
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